Getting Started With Pytorch In Google Collab With Free GPU

Abstraction: Beginner tutorial on PyTorch tensors and autograd using free Colab GPU

Key points:

• PyTorch is developed primarily by Facebook's AI research group; built on Torch (Lua-based); Uber's Pyro probabilistic language runs on it
• Core features: n-dimensional GPU-accelerated Tensors (like NumPy) and automatic differentiation (autograd) for backpropagation
• Google Colab provides free GPU (Tesla T4) with 12-hour execution windows and 60-minute idle timeout; released publicly October 2017
• PyTorch Tensors bridge seamlessly with NumPy via .numpy() and torch.from_numpy(); they share underlying memory
• Autograd uses define-by-run framework: backpropagation is defined dynamically by how code runs, via requires_grad=True and .backward()

Connections: Pytorch · Google Colab · Deep Learning · Automatic Differentiation · GPU Computing

Source: https://www.marktechpost.com/2019/06/09/getting-started-with-pytorch-in-google-collab-with-free-gpu/